Salesforce Adds Capabilities to Data Cloud

Salesforce today introduced several Data Cloud innovations that iinclude native processing of audio and video content, such as webinars and calls; a standardized semantic data model that enables Agentforce Agents and humans to interpret and use data consistently; improved search capabilities that factor in customer context; real-time data activations; and additional data security and governance features.

"In this new era of AI and agents, customer data and metadata are the new gold for the enterprise," said Rahul Auradkar, executive vice president and general manager of Data Cloud at Salesforce, in a statement. "Every day, more companies are using Data Cloud to unify all their data, from customer interactions and product usage to IoT and social media data, to gain deeper customer insights across all touchpoints and channels. Because Data Cloud is the foundation of Salesforce, companies can act on data to create the most personalized and meaningful customer experiences."

Data Cloud customers now have access to new capabilities and enhancements that make data accessible and actionable across every Salesforce activation, including the following:

• Support for unstructured audio and video content like customer calls, training sessions, product demos, feedback surveys, voicemails, and webinars.
• Data Cloud connectivity ecosystem expansion that allows organizations to bring their own data using additional pre-built Data Cloud connectors for apps like Square, Stripe, Meta, Splunk, and more. They can also tap into unstructured data from Google Drive, Microsoft SharePoint, Confluence, and Sitemap into Data Cloud using pre-built integrations provided with MuleSoft Direct for Data Cloud.
• Sub-second real-time layer that allows organizations to ingest, unify, analyze, and act on data in real time across Salesforce. This powers Einstein Personalization, now built on Data Cloud, along with real-time AI recommendations, analytics, and automations.
• Governance and security for trusted data and AI to improve how structured and unstructured data are managed, protected, and securely shared with AI applications and across the platform.
• Tableau Semantics, allowing organizations to organize data based on its meaning and relationships, creating a standardized semantic model that allows anyone to understand, use, and act upon data consistently, regardless of origin.
• Hybrid search, allowing organizations to find the most relevant information in their knowledge bases by combining semantic capabilities of vector search with the exact match capabilities of keyword search across any medium, such as PDFs, pictures, audios, and videos.
• Data Cloud One, allowing organizations to connect multiple Salesforce orgs that might be siloed across departments, regions, or business units and extend all of Data Cloud's functionalities across all Salesforce instances using a no-code, point-and-click setup. This allows them to create a single Data Cloud instance as the source of truth, enabling data sharing and actions, like automation, calculated insights, and more across all Salesforce orgs, without creating new Data Clouds.
• A new Datablazer community, an online platform to connect IT and business leaders, developers, and Data Cloud enthusiasts to learn, share insights, and stay informed on the latest best practices, trends, and tools to maximize the value of data.